Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively communicates the destructive nature ('cannot be undone') and the need for caution, which are critical for a mutation tool. However, it lacks details on permissions, rate limits, or error conditions that would further inform usage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise with two sentences that are front-loaded and zero waste. The first sentence states the purpose, and the second adds crucial behavioral context, making every word earn its place without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (destructive operation with no annotations and no output schema), the description is adequate but has gaps. It covers the irreversible nature but lacks details on what 'memories' entail, confirmation mechanics beyond the schema, or expected outcomes, leaving some contextual information incomplete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, with the 'confirm' parameter fully documented in the schema. The description does not add any additional meaning or context about parameters beyond what the schema provides, so it meets the baseline score of 3 for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Clear') and resource ('all stored memories'), distinguishing it from siblings like delete_memory (which targets individual memories) and list_memories (which is read-only). It precisely defines the scope as 'all' rather than selective deletion.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context with 'Use with caution as this cannot be undone,' indicating high-risk scenarios. However, it does not explicitly mention when to use alternatives like delete_memory for targeted removal or list_memories for verification, leaving some guidance implicit rather than explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden but only states the action ('Delete') without disclosing critical behavioral traits. It doesn't mention whether deletion is permanent, requires specific permissions, has side effects, or returns confirmation. For a destructive operation, this is a significant gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero wasted words. It's appropriately sized for a simple tool and front-loads the essential action and resource.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a destructive tool with no annotations and no output schema, the description is incomplete. It doesn't address behavioral risks, return values, or differentiation from siblings. Given the complexity of deletion operations, more context is needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds minimal value beyond the input schema, which has 100% coverage and fully documents the single parameter 'id'. The description restates that an ID is needed but doesn't provide additional context like ID format or sourcing.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Delete') and resource ('a specific memory by its ID'), making the purpose unambiguous. However, it doesn't differentiate from sibling tools like 'clear_memories' (which likely deletes multiple memories) or explain what constitutes a 'memory' in this context.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like 'clear_memories' or 'store_memory'. It lacks context about prerequisites (e.g., needing an existing memory ID) or exclusions (e.g., not for bulk deletion).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves statistics, implying a read-only operation, but doesn't specify whether this requires authentication, has rate limits, or details about the return format (e.g., structure of the statistics). The mention of 'tags, etc.' hints at additional data but lacks concrete behavioral traits like performance implications or error conditions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that directly states the tool's function without unnecessary words. It's front-loaded with the core purpose and includes helpful examples ('total count, tags, etc.') that add value. However, it could be slightly more structured by explicitly separating purpose from usage context.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (0 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on behavioral aspects like authentication or return format, which are important even for simple tools. With no output schema, the description doesn't explain what 'statistics' entail, leaving gaps in completeness for agent invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has 0 parameters, and schema description coverage is 100%, so there's no need for parameter documentation in the description. The description appropriately doesn't discuss parameters, focusing instead on the tool's purpose. A baseline of 4 is applied for zero-parameter tools, as no compensation is needed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with a specific verb ('Get') and resource ('statistics about stored memories'), including examples of what statistics are returned ('total count, tags, etc.'). It distinguishes from siblings like 'list_memories' or 'search_memories' by focusing on aggregated statistics rather than individual memory retrieval. However, it doesn't explicitly contrast with all siblings (e.g., 'clear_memories' is clearly different, but the distinction from 'list_memories' could be more explicit).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention scenarios where statistical overview is preferred over listing or searching memories, nor does it reference sibling tools like 'list_memories' or 'search_memories' for comparison. There's no indication of prerequisites, timing, or exclusions for usage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool lists memories with optional filtering, but doesn't describe what a 'memory' entails, how results are returned (e.g., pagination, format), or any constraints like rate limits or permissions. This leaves significant gaps for an agent to understand the tool's behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose ('List all stored memories') and adds a useful detail ('with optional filtering by tags'). There is no wasted language, making it highly concise and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what a 'memory' is, how results are structured, or any behavioral traits like default ordering or error handling. For a tool with two parameters and no structured output information, more context is needed to guide an agent effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description mentions optional filtering by tags, which aligns with the 'tags' parameter in the schema. With 100% schema description coverage, the schema already documents both parameters ('tags' and 'limit') clearly. The description adds minimal value beyond the schema, so a baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('List') and resource ('all stored memories'), making the purpose immediately understandable. It distinguishes from siblings like 'search_memories' by specifying 'all stored memories' rather than a search operation, though it doesn't explicitly contrast with other siblings like 'get_memory_stats'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It mentions optional filtering by tags, but doesn't specify when to use 'list_memories' versus 'search_memories' or other siblings, nor does it mention prerequisites or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool 'Returns relevant memories that match the search criteria,' which implies a read-only operation, but doesn't cover important aspects like permissions, rate limits, error handling, or what constitutes a 'relevant' match. For a search tool with zero annotation coverage, this is insufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and front-loaded, consisting of two clear sentences: one stating the purpose and one stating the return behavior. There is no wasted text, and every sentence earns its place by providing essential information efficiently.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (a search function with 3 parameters) and the absence of both annotations and an output schema, the description is incomplete. It doesn't explain the return format, how results are ordered, or any limitations (e.g., partial matches, case sensitivity). For a tool with no structured behavioral data, more detail is needed to be fully helpful.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description mentions 'keywords or tags,' which aligns with the 'query' and 'tags' parameters in the schema. However, schema description coverage is 100%, meaning the schema already fully documents all parameters. The description adds minimal value beyond what the schema provides, so it meets the baseline score of 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Search through stored memories using keywords or tags.' It specifies the verb ('Search'), resource ('stored memories'), and method ('using keywords or tags'). However, it doesn't explicitly differentiate from sibling tools like 'list_memories' or 'get_memory_stats,' which prevents a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to prefer 'search_memories' over 'list_memories' or other siblings, nor does it specify prerequisites or exclusions. This lack of contextual direction leaves the agent with minimal usage guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that the tool stores information for future use, implying persistence, but fails to describe key behavioral traits such as how memories are stored (e.g., durability, access controls), potential limitations (e.g., storage capacity, rate limits), or what happens on success/failure. This leaves significant gaps for a mutation tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized with two sentences that are front-loaded with the core purpose. Every sentence earns its place by explaining what the tool does and its intended use, though it could be slightly more structured by separating usage guidelines into a distinct part.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (a mutation tool with no annotations and no output schema), the description is incomplete. It lacks details on behavioral aspects like how memories are stored, any prerequisites (e.g., authentication), or what the tool returns. With no output schema to explain return values, the description should provide more context to be fully helpful.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all three parameters ('content', 'tags', 'metadata') with their types and optionality. The description adds no additional meaning beyond this, such as examples of valid content or metadata usage. Baseline 3 is appropriate when the schema handles parameter documentation effectively.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with a specific verb ('Store') and resource ('memory or piece of knowledge'), and provides examples of what can be stored ('important information, facts, preferences, or context'). However, it doesn't explicitly differentiate this from sibling tools like 'clear_memories' or 'delete_memory', which prevents a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides implied usage guidance by stating 'Use this to remember important information... for future conversations,' which suggests when to use it. However, it lacks explicit guidance on when not to use it or alternatives among the sibling tools, such as when to use 'search_memories' instead for retrieval.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.